Selected article for: "exponential growth and logistic growth model"

Author: Gillman, M.; Crokidakis, N. P.
Title: Dynamics and future of SARS-CoV-2 in the human host
  • Cord-id: nwezsoqz
  • Document date: 2020_7_17
  • ID: nwezsoqz
    Snippet: Forecasting trends in COVID-19 infections is vital for the global economy, national governments and physical and mental well-being. Using the per capita number of new cases as a proxy for the abundance of the SARS-CoV-2 virus, and the number of deaths as a measure of virulence, the dynamics of the pandemic and the outcomes emerging from it are examined for three locations (England, Italy and New York State). The data are analysed with a new version of a population dynamics model that combines ex
    Document: Forecasting trends in COVID-19 infections is vital for the global economy, national governments and physical and mental well-being. Using the per capita number of new cases as a proxy for the abundance of the SARS-CoV-2 virus, and the number of deaths as a measure of virulence, the dynamics of the pandemic and the outcomes emerging from it are examined for three locations (England, Italy and New York State). The data are analysed with a new version of a population dynamics model that combines exponential/logistic growth with time-varying carrying capacity, allowing predictions of persistence or extinction of the virus. In agreement with coevolutionary theory, the model suggests a transition from exponential virus growth to low abundance, coupled with reduced virulence, during colonisation of the alternate human host. The structure of the model allows a straightforward assessment of key parameters, which can be contrasted with standard epidemiological models and interpreted with respect to ecological and evolutionary processes and isolation policies.

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